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Enhanced free space detection in multiple lanes based on single CNN with scene identification [article]

Fabio Pizzati, Fernando García
2019 arXiv   pre-print
We propose a novel approach that estimates the free space inside each lane, with a single CNN.  ...  On the other hand, free space detection algorithms only detect navigable areas, without information about lanes.  ...  Proposed approach We propose an alternative approach: we directly detect all the pixels belonging to the road area in each lane, with a single CNN.  ... 
arXiv:1905.00941v2 fatcat:6j4zwcwcnbcsfhqqfys53nju2u

Vision-Based Autonomous Vehicle Systems Based on Deep Learning: A Systematic Literature Review

Monirul Islam Pavel, Siok Yee Tan, Azizi Abdullah
2022 Applied Sciences  
, pedestrian detection, lane and curve detection, road object localization, traffic scene analysis), decision making, end-to-end controlling and prediction, path and motion planning and augmented reality-based  ...  navigation and enhanced safety with overlapping on vehicles and pedestrians in extreme visual conditions to reduce collisions.  ...  Among all the deep learning methods, LetNet-5-based CNN on self-made dataset with spatial threshold segmentation with the HSV color space and Gabor filter on the GTSRB dataset performed best for traffic-sign  ... 
doi:10.3390/app12146831 fatcat:qkeylw67sngrtmmgwa2r3ue3ii

A Self-Calibrating Probabilistic Framework for 3D Environment Perception Using Monocular Vision

Razvan Itu, Radu Danescu
2020 Sensors  
The main contributions presented in this paper are the following: A method for generating the probabilistic measurement model from monocular images, based on CNN segmentation, which takes into account  ...  The system combines the strength of Convolutional Neural Network (CNN)-based segmentation with a generic probabilistic model of the environment, the dynamic occupancy grid.  ...  Comparison with Other Obstacle Detection Techniques In Table 7 we present a comparison of our system with other state-of-the-art object detection methods, based on features and capabilities.  ... 
doi:10.3390/s20051280 pmid:32120868 pmcid:PMC7085646 fatcat:sbt725qv5bhlxnqvda6hu2jpo4

2019 Index IEEE Transactions on Circuits and Systems for Video Technology Vol. 29

2019 IEEE transactions on circuits and systems for video technology (Print)  
Shen, W., +, TCSVT July 2019 2012-2028 Benchmark testing Iterative Multiple Hypothesis Tracking With Tracklet-Level Association. Improved Search in Hamming Space Using Deep Multi-Index Hashing.  ...  ., +, TCSVT Aug. 2019 2215-2228 Ultra-Low Complexity Block-Based Lane Detection and Departure Warning System.  ... 
doi:10.1109/tcsvt.2019.2959179 fatcat:2bdmsygnonfjnmnvmb72c63tja

A Review of Tracking and Trajectory Prediction Methods for Autonomous Driving

Florin Leon, Marius Gavrilescu
2021 Mathematics  
Approaches based on deep neural networks and others, especially stochastic techniques, are reported.  ...  Specifically, we focus on two aspects extensively explored in the related literature: tracking, i.e., identifying pedestrians, cars or obstacles from images, observations or sensor data, and prediction  ...  It is worth noting that a strictly CNN-based method needs substantial tweaking and careful parameter adjustment before it can accomplish the complex task of consistent detection in space and across multiple  ... 
doi:10.3390/math9060660 fatcat:qvikrr32tzd7fnjzs22u3ago4m

A Vision-Based Driver Assistance System with Forward Collision and Overtaking Detection

Huei-Yung Lin, Jyun-Min Dai, Lu-Ting Wu, Li-Qi Chen
2020 Sensors  
The proposed techniques consist of lane change detection, forward collision warning, and overtaking vehicle identification.  ...  In this paper, we present a vision-based system for driving assistance. A front and a rear on-board camera are adopted for visual sensing and environment perception.  ...  Unlike the conventional radar-based approaches [16] , our vision-based system can enhance the performance of existing object identification and lane detection techniques.  ... 
doi:10.3390/s20185139 pmid:32916970 pmcid:PMC7570579 fatcat:g4zauk2ntjhkxl3seozjn35244

Real-Time Physics-Based Removal of Shadows and Shading From Road Surfaces

Bruce A. Maxwell, Casey A. Smith, Maan Qraitem, Ross Messing, Spencer Whitt, Nicolas Thien, Richard M. Friedhoff
2019 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)  
For both types, the classifier trained on the illuminationfree outputs performs better, even on images with no cast shadows.  ...  We present a real-time physics-based system for generating an illumination free representation of road surfaces that maintains the distinction between asphalt and painted road markings.  ...  (c) and (d) show curves for the RF and CNN classifiers detecting white paint on only test images with no shadows. Figure 7 . 7 Figure 7.  ... 
doi:10.1109/cvprw.2019.00167 dblp:conf/cvpr/MaxwellSQMWTF19 fatcat:2b3aw3xpjjda7oi3wkhzj6wc7u

A Hybrid Vision-Map Method for Urban Road Detection

Carlos Fernández, David Fernández-Llorca, Miguel A. Sotelo
2017 Journal of Advanced Transportation  
The objective of this paper is to create a new environment perception method to detect the road in urban environments, fusing stereo vision with digital maps by detecting road appearance and road limits  ...  Even though our approach is based on machine learning techniques, the features are calculated from different sources (GPS, map, curbs, etc.), making our system less dependent on the training set.  ...  free space limit.  ... 
doi:10.1155/2017/7090549 fatcat:iwm7uhhtv5ge3eisuutezxtlqa

A Comprehensive Review on 3D Object Detection and 6D Pose Estimation with Deep Learning

Sabera Hoque, MD. Yasir Arafat, Shuxiang Xu, Ananda Maiti, Yuchen Wei
2021 IEEE Access  
Li [139] has come 970 up with an idea called GS3D, a 3DOD method based on an RGB (single) image in autonomous driving.  ...  It is a multi-philosophy fusion framework with a single philosophical ambiguity and quick guess selection based on a voting scheme.  ... 
doi:10.1109/access.2021.3114399 fatcat:kvdwsslqxff3lkh27tsdsciqma

Autonomous Vehicles Perception (AVP) Using Deep Learning: Modeling, Assessment, Challenges

Hrag-Harout Jebamikyous, Rasha Kashef
2022 IEEE Access  
The experiments are performed on a single TITAN X Pascal GPU. In [24] , the authors proposed an object detection and identification method.  ...  They registered each vehicle-free LIDAR scan to a global coordinate based on the GPS data to reconstruct a vehicle-free 3D point map.  ... 
doi:10.1109/access.2022.3144407 fatcat:27zpuomnxzbs3gl3ab55a46wru

A Survey on Theories and Applications for Self-Driving Cars Based on Deep Learning Methods

Jianjun Ni, Yinan Chen, Yan Chen, Jinxiu Zhu, Deena Ali, Weidong Cao
2020 Applied Sciences  
Then the main problems in self-driving cars and their solutions based on deep learning methods are analyzed, such as obstacle detection, scene recognition, lane detection, navigation and path planning.  ...  In recent years, more and more deep learning-based solutions have been presented in the field of self-driving cars and have achieved outstanding results.  ...  In order to deal with complex noises and scenes in the lane detection for self-driving cars, lots of methods based on deep learning have been proposed. For example, Xiao, et al.  ... 
doi:10.3390/app10082749 fatcat:iohm7uqj2vbojmnao6kyhzeliu

Deep Learning Serves Traffic Safety Analysis: A Forward-looking Review [article]

Abolfazl Razi, Xiwen Chen, Huayu Li, Hao Wang, Brendan Russo, Yan Chen, Hongbin Yu
2022 arXiv   pre-print
This processing framework includes several steps, including video enhancement, video stabilization, semantic and incident segmentation, object detection and classification, trajectory extraction, speed  ...  Besides, we investigate connections to the closely related research areas of drivers' cognition evaluation, Crowd-sourcing-based monitoring systems, Edge Computing in roadside infrastructures, Automated  ...  The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.  ... 
arXiv:2203.10939v2 fatcat:oml733wvjfh3blne4h7kg5y3du

Autonomous Driving with Deep Learning: A Survey of State-of-Art Technologies [article]

Yu Huang, Yue Chen
2020 arXiv   pre-print
Due to the limited space, we focus the analysis on several key areas, i.e. 2D and 3D object detection in perception, depth estimation from cameras, multiple sensor fusion on the data, feature and task  ...  This is a survey of autonomous driving technologies with deep learning methods.  ...  [105] is a proposal-free, single-stage detector by also representing the scene from the BEV.  ... 
arXiv:2006.06091v3 fatcat:nhdgivmtrzcarp463xzqvnxlwq

Steering Angle Prediction Techniques for Autonomous Ground Vehicles: A Review

Hajira Saleem, Faisal Riaz, Leonardo Mostarda, Muaz A. Niazi, Ammar Rafiq, Saqib Saeed
2021 IEEE Access  
The main difficulty in this regard is to identify the drivable road area on heterogeneous road types varying in color, texture, illumination conditions, and lane marking types.  ...  Unintentional lane departure accidents are one of the biggest reasons for the causalities that occur due to human errors.  ...  CNNs are basically proficient in analyzing visual imagery. The basic structure of a CNN has an input and an output layer, as well as multiple hidden layers.  ... 
doi:10.1109/access.2021.3083890 fatcat:hqoa37kbobbqrdgm23p3rfubcq

Convolutional Neural Network-based Optical Camera Communication System for Internet of Vehicles [article]

Amirul Islam
2019 arXiv   pre-print
However, most of the OCC applications are limited to single vehicle and there has been limited focus on the use of multiple vehicles detection (spatial) or fast processing (temporal) systems.  ...  In this research, a vision camera and high-speed camera has been proposed to provide multiple vehicle detection and fast data processing.  ...  Interference-free communication: scene. 2.  ... 
arXiv:1911.09529v1 fatcat:yjnq6u4bkjakzhcuikd5h53noq
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